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Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions

The aim of this paper is to characterise the fatigue reliability for various random strain loads under extreme value distribution while considering the cycle sequence effect condition in fatigue life prediction. The established strain–life models, i.e., Morrow and Smith–Watson–Topper, considered a m...

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Autores principales: Abdullah, Lennie, Karam Singh, Salvinder Singh, Abdullah, Shahrum, Ariffin, Ahmad Kamal, Zainal, Syifa Syuhaidah Meor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9822308/
https://www.ncbi.nlm.nih.gov/pubmed/36614795
http://dx.doi.org/10.3390/ma16010456
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author Abdullah, Lennie
Karam Singh, Salvinder Singh
Abdullah, Shahrum
Ariffin, Ahmad Kamal
Zainal, Syifa Syuhaidah Meor
author_facet Abdullah, Lennie
Karam Singh, Salvinder Singh
Abdullah, Shahrum
Ariffin, Ahmad Kamal
Zainal, Syifa Syuhaidah Meor
author_sort Abdullah, Lennie
collection PubMed
description The aim of this paper is to characterise the fatigue reliability for various random strain loads under extreme value distribution while considering the cycle sequence effect condition in fatigue life prediction. The established strain–life models, i.e., Morrow and Smith–Watson–Topper, considered a mean stress effect and strain amplitude; nevertheless, it excluded the load sequence effect, which involves the fatigue crack closure that is subjected to overload or underload. A FESEM-EDX analysis is conducted to characterise the failure features that occurred on the leaf spring. A finite element is simulated to determine the critical region in order to obtain the strain load behaviour. In addition, the strain signal is captured experimentally at 500 Hz for 100 s under operating conditions for three different road loads based on the critical location obtained from the finite element analysis. The fatigue life correlation shows that the Pearson correlation coefficients are greater than 0.9, which indicates the effective strain damage model is linearly correlated with the strain–life models. The fatigue life data are modelled using extreme value distribution by considering the random strain loads as extreme data. The reliability rate for the fatigue life is reported to be more than 0.59 within the hazard rate range of 9.6 × 10(−8) to 1.2 × 10(−7) based on the mean cycle to the failure point. Hence, the effective strain damage model is proposed for a fatigue reliability assessment under extreme conditions with higher reliability and provides fatigue life prediction when subjected to cycle sequence effects.
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spelling pubmed-98223082023-01-07 Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions Abdullah, Lennie Karam Singh, Salvinder Singh Abdullah, Shahrum Ariffin, Ahmad Kamal Zainal, Syifa Syuhaidah Meor Materials (Basel) Article The aim of this paper is to characterise the fatigue reliability for various random strain loads under extreme value distribution while considering the cycle sequence effect condition in fatigue life prediction. The established strain–life models, i.e., Morrow and Smith–Watson–Topper, considered a mean stress effect and strain amplitude; nevertheless, it excluded the load sequence effect, which involves the fatigue crack closure that is subjected to overload or underload. A FESEM-EDX analysis is conducted to characterise the failure features that occurred on the leaf spring. A finite element is simulated to determine the critical region in order to obtain the strain load behaviour. In addition, the strain signal is captured experimentally at 500 Hz for 100 s under operating conditions for three different road loads based on the critical location obtained from the finite element analysis. The fatigue life correlation shows that the Pearson correlation coefficients are greater than 0.9, which indicates the effective strain damage model is linearly correlated with the strain–life models. The fatigue life data are modelled using extreme value distribution by considering the random strain loads as extreme data. The reliability rate for the fatigue life is reported to be more than 0.59 within the hazard rate range of 9.6 × 10(−8) to 1.2 × 10(−7) based on the mean cycle to the failure point. Hence, the effective strain damage model is proposed for a fatigue reliability assessment under extreme conditions with higher reliability and provides fatigue life prediction when subjected to cycle sequence effects. MDPI 2023-01-03 /pmc/articles/PMC9822308/ /pubmed/36614795 http://dx.doi.org/10.3390/ma16010456 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Abdullah, Lennie
Karam Singh, Salvinder Singh
Abdullah, Shahrum
Ariffin, Ahmad Kamal
Zainal, Syifa Syuhaidah Meor
Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions
title Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions
title_full Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions
title_fullStr Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions
title_full_unstemmed Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions
title_short Fatigue Reliability Characterisation of Effective Strain Damage Model Using Extreme Value Distribution for Road Load Conditions
title_sort fatigue reliability characterisation of effective strain damage model using extreme value distribution for road load conditions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9822308/
https://www.ncbi.nlm.nih.gov/pubmed/36614795
http://dx.doi.org/10.3390/ma16010456
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